Five principles to get undergraduates involved in real-world data science projects
As a D-Lab and Data Science Education Program Fellow at the University of California, Berkeley in Spring 2020, I helped to ensure and enhance the quality of more than 40 Data Science Discovery Projects, working with community partners and undergraduate research assistants. The goal of these projects was to connect undergraduates with community impact groups, entrepreneurship ventures, and educational initiatives across UC Berkeley and provide them with hands-on and team-based research opportunities outside the classroom.
In a pandemic, what use is Google?
This blog by Sam Gilbert explains how internet search data is being used in responses to the Covid-19 pandemic, and what search datasets and tools are available to researchers.
Adapting your qualitative methods course for online learning
There’s a lot of uncertainty about how higher education will be taught in the age of COVID-19. How should professors and instructors of qualitative methods courses re-think their curriculums for online classrooms or cohorts? How can students conduct observations if they’re sheltered at home? How will students work in teams to analyze data if they’re distributed across the world? Here are some tips for alternative data collection methods, and collaborative tools for remote analysis.
Moving your behavioral research online
COVID-19 has affected research all over the world. With universities closing their campuses and governments issuing restrictions on social gatherings, behavioral research in the lab has ground to a halt. This situation is urgent. Ongoing studies have been disrupted and upcoming studies cannot begin until they are adapted to the new reality. At Volunteer Science, we’re helping researchers around the world navigate these changes. In this post, I’ll condense the most important recommendations we’re giving to researchers for translating their studies into an online format and recruiting virtual participants.
SAGE Concept Grants: Interviews with our £2,000 winners
The SAGE Concept Grants form an integral part of our mission at SAGE Ocean to support the use of computational methods and big data in social science research. Read interviews with the winners to find out how their tools will benefit social research, and how the funding from SAGE will help them.
Interview with Concept Grant 2020 winner: Knowsi
SAGE has announced the 2020 winners of its Concept Grant program, which provides funding for innovative software solutions that support social science research. In this blog we interview Andrew Lovett-Barron, the creator of the winning tool, Knowsi; a portal for researchers and participants to manage their consent relationship.
Turning COVID-19 into a data visualization exercise for your students
We will emerge from this pandemic with a better understanding of the world and an improved ability to teach others about it. For now, we need to be continuously analyzing the data and thinking about the lessons we can learn and apply. Here’s how you can join in!
At SAGE, we have been working with academics around improving and sharing teaching resources, especially for quantitative and computational methods in social sciences. Besides the mass remote and emergency teaching experiment happening right now, one of the positive things we can already identify and reuse to improve learning in methods courses is the glut of data visualizations. The absolute advantage here is that all these visualizations are produced (almost always) with the same raw input, telling a variety of different stories. What better way to explain the different uses and impact of visualizations and the use of different tools to students than examples based on the same data?
How will COVID-19 impact student research projects?
Around the world, higher education faculty and students have been grappling with the mammoth task of flipping from face-to-face teaching to online learning, practically overnight. As teaching faculty scramble to figure out how to use Zoom for online learning and the debate continues as to whether universities should cancel exams or switch to home-based open book or open Google exams, it’s becoming clear that the impact of COVID-19 on academic research could be just as profound as the impact on teaching. In-person lab experiments, face-to-face interviews, focus groups, fieldwork and other data collection may be impossible for much of 2020. Where possible, researchers will switch modes from face-to-face to virtual or telephone data collection, and where that’s not possible or desirable for practical or methodological reasons, university research offices and funders are issuing guidance for academics who need to delay their data collection or fieldwork.
Resources for visualizing and mapping COVID-19 data
Research communities across the globe are tirelessly collecting, analyzing and sharing data to help us understand and tackle the coronavirus pandemic. Here’s a collection of resources that visualize, map and demystify COVID-19 data.
From preprocessing to text analysis: 80 tools for mining unstructured data
Text mining techniques have become critical for social scientists working with large scale social data, be it Twitter collections to track polarization, party documents to understand opinions and ideology, or news corpora to study the spread of misinformation. In the infographic shown in this blog, we identify more than 80 different apps, software packages, and libraries for R, Python and MATLAB that are used by social science researchers at different stages in their text analysis project. We focused almost entirely on statistical, quantitative and computational analysis of text, although some of these tools could be used to explore texts for qualitative purposes.